Browsing by Author "Qu, D"

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    Quantifying moisture recycling of a leeward oasis in arid central Asia using a Bayesian isotopic mixing model
    (Elsevier, 2022-10) Wang, S; Wang, L; Zhang, MJ; Shi, Y; Hughes, CE; Crawford, J; Zhou, J; Qu, D
    Locally recycled moisture from transpiration and surface evaporation is of great importance in the terrestrial hydrological cycle, especially in the widely distributed oases across arid central Asia. Quantitative assessment of the proportional contribution of recycled moisture to local precipitation, i.e., the recycling ratio, is useful to understand the land-air interaction as well as the anthropogenic impact on the regional water cycle. Here we analyzed the stable hydrogen and oxygen isotopes in precipitation samples collected at six stations across the Kaxgar-Yarkant Oasis in the western Tarim Basin of central Asia from April 2018 to June 2020. Using this data, the moisture recycling ratio in this typical oasis was assessed using a Bayesian three-component isotopic mixing model. For the plain stations, the annual weighted mean δ18O value in precipitation ranged from −5.94 ‰ to −1.46 ‰, and the mountain station has a lower annual mean precipitation isotopic ratio. The average recycling ratio during the summer months ranged between 17.0 % and 63.9 % for each sampling station in the Kaxgar-Yarkant Oasis, and the proportional contribution from transpiration ranged from 15.1 % to 61.3 %. The contribution of plant transpiration to local precipitation is much larger than that of surface evaporation. The recycled portion in total precipitation amount may increase the local precipitation under an oasis expansion background but is insufficient to change the arid background. In addition, the Bayesian isotopic mixing model is promising to determine the recycling ratio in an arid setting, and provides more spatial details than the climate reanalysis-based calculation. © 2022 Elsevier B.V.
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    Spatial and seasonal isotope variability in precipitation across China: monthly isoscapes based on regionalized fuzzy clustering
    (American Meteorological Society, 2022-06-01) Wang, S; Lei, S; Zhang, MJ; Hughes, CE; Crawford, J; Liu, ZF; Qu, D
    The spatial patterns of stable hydrogen and oxygen isotopes in precipitation (precipitation isoscapes) provide a geographic perspective to understand the atmospheric processes in modern environment and paleoclimate records. Here we compiled stable isotope data in modern precipitation at 223 sites across China and 48 in surrounding countries, and used regionalized fuzzy clustering to create monthly precipitation isoscapes for China (C-Isoscape). Based on regressions using spatial and climatic parameters for 12 months, the best-fitting equations were chosen for four climate clusters, and then the four layers were weighted using fuzzy membership. The moisture transportation path, controlled by the westerlies and the monsoon, results in different spatial and seasonal diversity of precipitation isotopes. Based on C-Isoscape, we determined a nationwide meteoric water line asδ2H = 7.4δ18O + 5.5 using least squares regression orδ2H = 8.0δ18O + 10.2 using precipitation weighted reduced major axis regression. Compared with previous global products, the C-Isoscape usually shows precipitation more enriched in18O and2H in summer and more depleted in winter for northwest China, while the C-Isoscape values are more enriched in heavy isotopes in most months for southwest China. The new monthly precipitation isoscapes provide an accurate and high-resolution mapping for Chinese precipitation isotopes, allowing for future intra-annual atmospheric process diagnostics using stable hydrogen and oxygen isotope in precipitation in the region. Ó 2022 American Meteorological Society.